Low rates of bacterivory enhances phototrophy and competitive advantage for mixoplankton growing in oligotrophic waters

With climate change, oceans are becoming increasingly nutrient limited, favouring growth of prokaryotic picoplankton at the expense of the larger protist plankton whose growth support higher trophic levels. Constitutive mixoplankton (CM), microalgal plankton with innate phototrophic capability coupled with phagotrophy, graze on these picoplankton, indirectly exploiting the excellent resource acquisition abilities of the prokaryotes. However, feeding rates can be very low (e.g., a few bacteria d−1). For the first time, the significance of such low consumption rates has been quantified. We find that while prokaryote-carbon (C) supply to CM grown at non-limiting light was so low that it may appear insignificant (< 10%), contributions of nitrogen (N) and phosphorus (P) from ingestions of 1–12 prokaryotes d−1 were significant. Under limiting light, contributions of ingested C increased, also raising the contributions of N and P. The order of nutritional importance for CM growth from predation was P > N > C. Further, provision of N through internal recycling of ingested prey-N stimulates C-fixation through photosynthesis. Importantly, coupled photo-phago-mixoplanktonic activity improved CM resource affinities for both inorganic and prey-bound nutrients, enhancing the nutritional status and competitiveness of mixoplankton. With warming oceans, with increased prokaryote abundance, we expect CM to exhibit more phagotrophy.

reference to sizes of the organisms (expressed as equivalent spherical diameter, ESD), and their motilities together with turbulence which together increase encounter rates. We assumed mixoplankton C:N:P stoichiometries (mass ratio of ca. 6.1:4.8:1) according to the phytoplankton analysis conducted by Geider and LaRoche (2002), noting that many flagellate 'phytoplankton' are actually mixoplankton (Unrein et al., 2014;Zubkov and Tarran, 2008;Leles et al., 2019). Bacteria C:N:P stoichiometries were obtained from Heldal et al. (1996), Tortell et al. (1996) and Zimmermann et al. (2014), and those for picophytoplankton from Bertilsson et al. (2003) and Cunningham and John (2017). Together, these references evidence differences in the C-density of bacteria and the prokaryote phytoplankton (Table S1), such that the latter are ca. 10-15% denser in terms of C and N, but contain half the amount of P.
We calculated the number of prokaryote cells required to be assimilated per CM predator cell per day to provide, at the extreme, all the structural C, N and P needed to support a doubling per day (i.e., for a growth rate of 0.693 d -1 ). To place this in context we have identified those combinations of prey and predator that could achieve that nutritional support through ingesting (on average) just 1 prey item per day, or 1 prey per hour. If we then consider combinations of predator and prey allometry and stoichiometry that support a growth rate of 0.693 d -1 at an ingestion rate of 1 prey h -1 , those same combinations, but at an ingestion rate of 1 prey d -1 , would support a growth rate of (0.693/24 =) 0.029 d -1 ; this value aligns with the minimum growth rate needed to compensate for a loss rate of the CM through mixing from the sunlit mixed layer into the meso-pelagic zone (e.g., Fasham et al., 1990). These calculations provide the most optimistic case, with a 100% efficiency for capture and assimilation to attain the maximum growth rate. In reality, the interactions between the different trophic modes are complex and intertwined (see Fig. 1), and growth rarely occurs at the maximum rate. To obtain an enhanced, more realistic appreciation of the potential for low rates of grazing requires the use of a mechanistic simulation model.

Simulation Model
The potential role for CM growth provided by phagotrophy upon prokaryotes coupled with phototrophy was explored using a simulation model developed from our earlier models (Flynn and Mitra, 2009;Mitra et al., 2021;Flynn and Mitra, 2023). These models have been deployed in various scenarios (Leles et al. 2018;Lin et al., 2018;Leles et al., 2021;Li et al., 2022). Our models are the only mixoplankton models to date that have been subjected to 'expert witness validation' (hence the authorship list in Mitra et al., 2014Mitra et al., , 2016, and tuning to empirical data (Lin et al., 2018;Li et al., 2022). The model thus conforms to aspirations for a digital twin description of these organisms (see Flynn et al., 2022).
The task at hand demands a comprehensive plausible description of C,N,P physiology, operating in an explicit light-dark cycle. Our mixoplankton models are the only ones to deliver to that need; the physiological system is complex with various layers of feedback such that gross simplifications will only introduce uncertainties.
The model is capable of resolving growth exploiting phototrophy, osmotrophy and phagotrophy ( Fig. 1; Mitra et al., 2021). It provides a full variable stoichiometric (C,N,P,Chl) description in which the simulated growth dynamics are modulated by feedback processes in line with the physiological acclimation processes that occur in reality. The model simulates the use of different nutrient types (inorganic and organic) under different illumination regimes.
Internal nutrient recycling, impacted by different supply and demand, and anabolic / catabolic respiration rates varying over the light:dark cycle, are described. There is an explicit inclusion of allometry for consideration of predation, and of the biomass allocation to photosystems (Fig. S1). The model features extensive modulation between submodules describing facets of the physiology, with functioning in keeping with biochemical understanding as described using a coarse-grain systems biology approach.
The model was constructed and run within Powersim Studio 10 software (Powersim Software AS, Norway), under Euler integration with a step size of 0.015625d. An example of the model operating in batch-culture mode, exploiting two different prey organisms, nitrate, ammonium and phosphate, is given in Fig. S2.

Functional Equations
The following provides a functional-equation description of the model as text strings, with the form: result = f{comma delimited list of factors involved in deriving the result} Underlined terms in the equations are rates. Those in bold donate terms that provide a positive interaction (i.e., the result increases when the term increases; these are usually enacted via a curvi-linear function); terms not in bold may involve negative or more complex interactions (such as bell-shaped for prey allometry affecting capture).
The equations are provided working backwards from the emergent organism growth rate, with descriptions of the steps enabling that rate to be attained. NOTE: For brevity, reference to state variables does not include 'prot'.
Total protist biomass C is given as, T C = M C+ PM C+ C C.

State variables
The model comprises the following state variables and associated flows: Depending on the application, additional state variables can be included: • protCells (cells m -3 ): cells, required for a dynamic description of cell-size with nutrient status, diel light cycle and temperature • protSi (mgSi m -3 ); organism-Si, required for diatoms • protANA (mgNA m -3 ); acquired nucleic acid material from phototrophic prey, required to support acquired phototrophy in plastidic specialist non-constitutive mixoplankton (pSNCM)

Growth and nutrient status
Ultimately growth is a function of the nutritional status of the organism (in terms of elements C, N and P) and the maximum growth rate potential. The latter varies with temperature, T, around the value of µmax at a reference temperature, µmaxRT. growth = f{C-status, N-status, P-status, µmax, losses} The nutrient status defines the health of the organism in terms of C ( M C: T C), N (N: T C) and P (P: T C), and is a function of various inputs and outputs. Inputs are associated with the use of dissolved organic substrates via osmotrophy, prey via phagotrophy, and also the use of inorganics via phototrophy. Losses occur through respiration and regeneration, and also through the leakage of metabolites as dissolved organic matter (DOM), some of which may be recovered via osmotrophy (Fig. S1).

Losses = f{C-respiration, N-regeneration, P-regeneration, DOM-leak}
Growth is associated with catabolic (including basal) and anabolic respiration, part of which is associated with specific dynamic action (SDA) during prey digestion and assimilation.
Anabolic respiration is affected by the flows of resources via the different trophic mechanisms.
Nitrate assimilation incurs an additional cost for reduction of nitrate to nitrite to ammonium.
There are also losses of C, N, P required to preserve organism stoichiometry within the bounds of acceptable C:N:P.
Cell division occurs when the cell reaches a critical size (which varies with nutrient status and temperature affecting the growth rate), and typically occurs in phototrophs within a specific part of the diel light:dark (LD) cycle. division = f{size, critical size, LD} critical size = f{T, C-status, N-status, P-status, growth} The size of the organism affects predation for phagotrophy, and whether it itself is likely to encounter its own predator.

Osmotrophy
Osmotrophy depends on the concentration of the substrate, [DOM], the C:N:P status of that material, and the uptake kinetics parameters of the maximum uptake rate ( DOM Vmax) and the substrate affinity (i.e., the reciprocal of the half saturation constant, KDOM). The uptake kinetics depend on the nutrient status of the organism; cells that are nutrient-stressed have a higher uptake potential and a high affinity. DOM-leak = f{C-status, N-status, osmotrophy, phagotrophy, phototrophy, µmax}

Phagotrophy and voiding
Phagotrophy brings in resources from the assimilation of prey biomass; note the plural in preyassimilations. Prey need to be encountered (which depends on the sizes of the predator organism and of the prey, their respective motilities and turbulence), captured (which like the predator motility varies with satiation, and also with the 'taste' of the prey as affected by its stoichiometric quality) and ingested. These processes are prey-species specific; the collective biomass from many ingestions, perhaps of different prey organisms, is then digested. During digestion a fraction of the ingested prey is subjected to voiding (depending on the assimilation efficiency, AE, predator satiation and the food quality), and another fraction is lost associated with specific dynamic action (SDA) as the prey biomass is subjected to catabolic and then anabolic processes. The internal recycling of regenerated inorganic nutrients is a critical step in mixoplankton ( Fig. S1; see Inorganic nutrient assimilations, below). The uptake of DIN is affected also by the P-status of the organism. The uptake kinetics for ammonium (NH4) provide for development of a much enhanced uptake capability over that for nitrate (NO3), with that development also commencing at a higher N-status. The latter results in ammonium being taken up 'in preference' to nitrate (there is no 'inhibition' term controlling NO3-assimilation by [NH4]); if the supply of ammonium from internal recycling plus external sources cannot meet the demand, then the ability to use nitrate is de-repressed.    Mixoplankton growth was supported by carbon (C), nitrogen (N), and phosphorus (P) from phototrophy (photosynthesis + NH4 + + DIP) and phagotrophy (prey C,N,P). Note the internal cycling of NH4 + and DIP (dissolved inorganic phosphorus) through catabolism which negates specific dynamic action (SDA). See also Supplementary Information S1. Panel (b) shows the chemostat setup with: (i) inflows of resources as inorganic nutrients and prey; (ii) growth of the mixoplankton exploiting these resources; (iii) outflow of residual resources and mixoplankton, and also of voided and regenerated wastes (not shown). Inflow and outflow dilution rates were the same, and at steady state this dilution rate sets (is equal to) the growth rate averaged over the 24 h light-dark cycle. Table S1. Prey allometry and stoichiometry. The carbon (C) per cell values were calculated from the general equation: pg C = a•(prey cell volume) ^b, where prey cell volume = 4/3 π(ESD/2)^3; values of a and b are indicated in the table; ESD: equivalent spherical diameter. i, Romanova & Sahzin, 2010;ii, Heywood et al., 2006;iii, Zimmermann et al., 2014;iv, Bertilsson et al., 2003;v, Tortell et al., 1996 Table S1 for stoichiometric values.  Table S1 for stoichiometric values.      Fig. 6 for all other details. This resource regime drives P-limitation of growth in the mixoplankton rather than N-limitation as in Fig. 6. In comparison with Fig. 6, the contributions from feeding to carbon and nitrogen are lower.

Fig. S11
Ingestion rates and fate of bacteria C,N,P biomass when CM predator or prokaryotic prey are smaller. As for Fig. 6, with 'Bac' the same as in that figure. Also shown here the situation with smaller bacteria (halved biomass; 0.8µm ESD rather than 1µm; 'sBac') and smaller CM (halved biomass, equating to ca. 4µm ESD rather than 5µm; 'sMixo'). See Fig. S12 for residual prey abundance.   Table S3. Examples of ingestion rates of bacteria into constitutive mixoplankton. Rates in the literature have been converted to common units of prey cells (predator cell) -1 d -1 . Sizes of the mixoplankton where not available from the references listed in the table, have been obtained from the Mixoplankton Database (Mitra et al., 2023). *Fluorescent Labelled Bacteria. The 'community' feeding rates reflect average feeding across the community of cells in the culture, recognising that statistically only a few cells are seen to be feeding. The 'feeding cells' is the ingestion rate amongst cells that are all actively feeding.